I describe a dataset with almost 1600 types of red wine, in order to understand the meaning of the assigned score.
This dataset is provided by Paulo Cortez, António Cerdeira, Fernando Almeida, Telmo Matos, and José Reis, from different universities in Portugal. It provides information like acidity, residual sugar, chlorides, and alcohol among others. I explore the data to find patterns and trends and get the meaning of the given features. More information here.
Let’s start showing some summary numbers and first histograms to understand individual variables.
This document is all about quality. Here is the distribution of wine by quality.
These histograms show how the values are distributed in the different variables.
# Statistical information about Volatile Acidity
summary(data$volatile.acidity)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.1200 0.3900 0.5200 0.5278 0.6400 1.5800There are a few outliers only on the right side.
# Statistical information about Fixed Acidity
summary(data$fixed.acidity)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 4.60 7.10 7.90 8.32 9.20 15.90There are several outliers only on the right side.
# Statistical information about Total Sulphure Dioxide
summary(data$total.sulfur.dioxide)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 6.00 22.00 38.00 46.47 62.00 289.00There are many outliers only on the right side.
# Statistical information about Alcohol
summary(data$alcohol)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.40 9.50 10.20 10.42 11.10 14.90There are just a few outliers only on the right side.
# Statistical information about Chlorides
summary(data$chlorides)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.01200 0.07000 0.07900 0.08747 0.09000 0.61100There are just a few outliers on the left side, and many on the right side.
# Statistical information about Residual Sugar
summary(data$residual.sugar)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.900 1.900 2.200 2.539 2.600 15.500There are many outliers on the right side.
# Statistical information about pH
summary(data$pH)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.740 3.210 3.310 3.311 3.400 4.010All values are pretty well distributed in the pH variable. There are several outliers on both sides.
# Statistical information about Sulphates
summary(data$sulphates)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.3300 0.5500 0.6200 0.6581 0.7300 2.0000There are many outliers only on the right side.
# Statistical information about Density
summary(data$density)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.9901 0.9956 0.9968 0.9967 0.9978 1.0037This variable is also well distributed. There are several outliers on both sides.
There are 9 continuous variables, 2 discrete variables and one ordered categorical variable: quality.
My general question is, how do chemical properties define the quality of the red wine?
There are interesting features in this dataset, each of them describing an important property of the red wine. Density, pH, sulphur dioxide, and sulphates are, in my opinion, the most important ones, in order to measure the quality. Let’s see what we can find by looking at those variables.
It was not necessary to clean missing values on this dataset. However, I think it is a good idea to apply some transformations to skewed variables.
Transformed Volatile Acidity using log base 10.
Transformed Tartaric Acid using log base 10.
Transformed Total Sulphure Dioxide using log base 10.
Transformed Chlorides using log base 10.
Transformed Residual Sugar using log base 10.
Transformed Sulphates using log base 10.
Transformed Free Sulphure Dioxide using log base 10.
Using the new variable durability, it’s possible to appreciate the effect of sulphates and free sulphure dioxide.
This variable has only two values: S (short) and L (large), using the median of sulphates and free sulphure dioxide as inflection point.
Let’s try to find trends and interesting patterns by comparing two variables.
cor(x = data$quality, y = data$alcohol)## [1] 0.4761663Fact: Higher quality wines seem to have higher levels of alcohol
# Correlation between Quality and Fixed Acidity
cor(x = data$quality, y = data$fixed.acidity)## [1] 0.1240516Fact: Higher quality wines seem to have lower levels of acidity
# Correlation between Quality and Density
cor(x = data$quality, y = data$density)## [1] -0.1749192Fact: Higher quality wines seem to have lower density
Citric Acid adds freshness flavor to the wine.
# Correlation between Citric Acid and pH
cor(x = data$citric.acid, y = data$pH)## [1] -0.5419041
Level of acetic acid. Too high levels make an unpleasant vinegar taste.
# Correlation between Volatile Acidity and pH
cor(x = data$volatile.acidity, y = data$pH)## [1] 0.2349373
# Correlation between Density and Quality
cor(x = data$density, y = data$quality)## [1] -0.1749192I’ve found a slightly positive correlation, meaning that density tends to be lower on high-quality wines. However, this correlation is not so important to determine the quality as shown by the correlation coefficient.
# Correlation between Chlorides and Sulphates
cor(x = data$chlorides, y = data$sulphates)## [1] 0.3712605I’ve found that levels are mostly low for both variables. I would say that they don’t influence much on the quality as all types of wine have the same level of these two variables.
# Correlation between Chlorides and Residual Sugar
cor(x = data$chlorides, y = data$residual.sugar)## [1] 0.05560954I’ve found the same here, as they keep levels constantly low and correlation coefficient is almost 0.
# Correlation between Free Sulphure Dioxide and Total Sulphure Dioxide
cor(x = data$free.sulfur.dioxide, y = data$total.sulfur.dioxide)## [1] 0.6676665Levels are always low. However, these two variables seem to be correlated.
So far I find only density to be an interesting variable to look at. The rest, chlorides, sulphates, residual sugar and sulphure dioxide don’t seem to be a great influence on wine quality.
This variable indicates the acidity level of the wine. The scale goes from 0 (very acid) to 14 (very basic). But most of red wines are statistically between 3 and 4.
Another point of view:
It’s quite surprising that levels of pH are lower on high-quality wines.
The level of this variable depends on alcohol percentage and sugar.
Another point of view:
Density levels are also lower on high-quality wines.
The free form of SO2 exists in equilibrium between molecular SO2 (as a dissolved gas) and bisulfite ion. It prevents microbial growth and the oxidation of the wine.
Another point of view:
Again, the levels for this variable are lower for both low-quality and high-quality wines.
Additive contributing with sulphure dioxide gas (S02) levels, acting as an antimicrobial and antioxidant.
Sulphates levels are lower for low-quality and high-quality wines as well.
A quite strong correlation can be observed between these two variables, regarding the quality of wines. Meaning that it’s normal to find lower levels of pH and density on high-quality wines. The lines colours let you see how durable the wine can be respect to alcohol, using the durability variable introduced above. It makes sense to me that wines last longer if they contains more alcohol in addition to sulphates and free sulphure dioxide.
I’ve found here another interesting correlation, which becomes quite obvious if we pay special attention to the meaning of the variables. Density, as I said above, is actually density of water. So, the more alcohol the less water. The coloured lines show that the durability of the wine is lower when the density of water is higher. Does it make sense?
## quality mean_quality mean_alcohol mean_density
## Min. :3.00 Min. :3.00 Min. : 9.90 Min. :0.9952
## 1st Qu.:4.25 1st Qu.:4.25 1st Qu.:10.03 1st Qu.:0.9962
## Median :5.50 Median :5.50 Median :10.45 Median :0.9966
## Mean :5.50 Mean :5.50 Mean :10.72 Mean :0.9965
## 3rd Qu.:6.75 3rd Qu.:6.75 3rd Qu.:11.26 3rd Qu.:0.9970
## Max. :8.00 Max. :8.00 Max. :12.09 Max. :0.9975
## mean_ph mean_citric_acid n
## Min. :3.267 Min. :0.1710 Min. : 10.00
## 1st Qu.:3.294 1st Qu.:0.1915 1st Qu.: 26.75
## Median :3.312 Median :0.2588 Median :126.00
## Mean :3.327 Mean :0.2715 Mean :266.50
## 3rd Qu.:3.366 3rd Qu.:0.3498 3rd Qu.:528.25
## Max. :3.398 Max. :0.3911 Max. :681.00
Something very remarkable to keep in mind is what this plot shows: high-quality wines seem to last longer. But the orange line on the top-right corner makes a huge difference. They last much longer when alcohol level is higher.
This is a pretty straight forward correlation. When pH level gets lower (which means that there is more acid) citric acid gets higher. It makes sense, doesn’t it?
I wanted to emphasize this plot again because levels of density look similar for both low-quality and high-quality wines. Or from another perspective, the density of water is higher only on mid-quality wines.
At the beginning it was for me quite difficult how to detect which levels of acids and minerals would be beneficial for the quality of wine. Understanding univariate visualisations helped me to find relationships and go deeper with the exploration comparing variables and finding correlations. Finally, after visualising bivariate plots, I could create even more advanced visualisations being able to display the trend of one variable regarding other two variables in the multivariate section.
I feel that now I have a few extra tips to select new wines to taste. Higher levels of alcohol and acidity, lower levels of density, as well as low levels of residual sugar, chlorides, and sulphates. High levels of alcohol and low level of density were definitely surprising for me. However, I think that the data set needs some more categorical variables and much more data to make better analysis.
For instance, adding columns with usual customers, sommeliers preferences, country of origin, types of grape, altitude of grape crops, and type of cask used to keep them before selling would be of great value to measure wine quality beyond the product itself, but also the background environment and production process.